Matteo Scandella

Position

PhD student

Email

matteo.scandella@unibg.it

Matteo Scandella was born in Clusone (BG), Italy, on 29th December 1992.
He received the Bachelor Degree in Computer Science Engineering in 2014 from the Università degli Studi di Bergamo (Italy) and the Master Degree in Computer Science Engineering in 2016, with a thesis about algorithms for the semi-supervised indetification of non linear dynamical system.

From October 2016 is a Ph.D student in Engineering and Applied Sciences at Università degli Studi di Bergamo.

Publications

2019
A note on the numerical solutions of kernel-based learning problems
M. Scandella, M. Mazzoleni, S. Formentin, F. Previdi

Submitted to IEEE Transactions on Automatic Control.

Condition monitoring using statistical process control methods of Electro-Mechanical Actuators with applications to More Electric Aircrafts
M. Mazzoleni, F. Previdi, M. Scandella, G. Pispola

Submitted to IEEE Transactions on Industrial Electronics.

Enhanced kernels for nonparametric identification of a class of nonlinear systems
M. Mazzoleni, M. Scandella, S. Formentin, F. Previdi

Submitted to 58th IEEE Conference on Decision and Control.

Experimental development of a Health Monitoring method for Electro-Mechanical Actuators of flight control primary surfaces in More Electric Aircrafts
M. Mazzoleni, F. Previdi, M. Scandella, G. Pispola

Submitted to IEEE Access.

Nonlinear system identication via data augmentation
S. Formentin, M. Mazzoleni, M. Scandella, F. Previdi

Systems & Control Letters, Vol. 128 (2019) pp. 56–63.
DOI: https://doi.org/10.1016/j.sysconle.2019.04.004
ISSN: 0167-6911

On the existence of alternative solutions for regularized kernel methods
M. Scandella, M. Mazzoleni, S. Formentin, F. Previdi

Submitted to 33rd Conference on Neural Information Processing Systems (NeurIPS) 2019, Vancouver (CAN).

2018
Classification of light charged particles via learning-based system identification
M. Mazzoleni, M. Scandella, S. Formentin, F. Previdi

57th IEEE Conference on Decision and Control (CDC), Miami Beach (FL), USA, 2018.
DOI: 10.1109/CDC.2018.8618946
ISBN: 978-1-5386-1395-5.

Condition monitoring of electro-mechanical actuators for aerospace using batch change detection algorithms
M. Mazzoleni, M. Scandella, Y. Maccarana, F. Previdi, G. Pispola, N. Porzi

Proceedings of the 2nd IEEE Conference on Control Technology and Applications (CCTA), Copenhagen (DK)
DOI: 10.1109/CCTA.2018.8511334
ISBN: 978-1-5386-7698-1

Condition assessment of electro-mechanical actuators for aerospace using relative density-ratio estimation
M. Mazzoleni, M. Scandella, Y. Maccarana, F. Previdi, G. Pispola, N. Porzi

Proceedings of the 18th IFAC Symposium on System Identification (SYSID), Stockholm (SE)
DOI: 10.1016/j.ifacol.2018.09.070
ISSN: 2405-8963

Identification of nonlinear dynamical system with synthetic data: a preliminary investigation
M. Mazzoleni, M. Scandella, S. Formentin, F. Previdi

Proceedings of the 18th IFAC Symposium on System Identification (SYSID), Stockholm (SE)
DOI:  10.1016/j.ifacol.2018.09.227 
ISSN: 2405-8963

Development and Experimental Testing of a Health Monitoring System of Electro-Mechanical Actuators for Small Airplanes
F. Previdi, Y. Maccarana, M. Mazzoleni, M. Scandella, G. Pispola, N. Porzi

Proceedings of the 26th Mediterranean Conference on Control and Automation (MED), Zadar (HR)
DOI: 10.1109/MED.2018.8442734
ISSN: 2473-3504

Semi-supervised learning of dynamical systems: a preliminary study
M. Mazzoleni, S. Formentin, M. Scandella, F. Previdi

Proceedings of the 17th IEEE European Control Conference (ECC), Lymassol (CY)
DOI: 10.23919/ECC.2018.8550550
ISBN: 978-3-9524-2698-2

Kernel manifold regression for the coupled electric drives dataset
M. Mazzoleni, M. Scandella, F. Previdi

3rd Nonlinear System Identification Benchmarks Workshop, Liege (BE)